miRNA Expression Data Research Articles

Identification of microRNAs related to myocardial ischemic reperfusion injury.

Previous studies have suggested that microRNAs (miRNAs) are associated with the progression of myocardial ischemic reperfusion (I/R) injury. However, inconsistent results have been obtained due to the differences in sequencing platform, control selection, and filtering conditions. To explore the key miRNAs in the pathogenesis of myocardial I/R injury and develop miRNA diagnostic biomarkers for myocardial I/R injury prevention, we performed a systematic analysis of publicly available myocardial I/R injury miRNA expression data and investigated the function of the signature miRNA. A total of 17 representative myocardial I/R injury miRNA datasets were extracted from the Google Scholar website and a systematic bioinformatics analysis was done. TargetScan software was used to predict the miRNA target genes, and functional enrichment and transcription factor binding analyses were performed on the target genes using the DAVID and Tfacts databases. In this study, a total of 10 signature miRNAs associated with myocardial I/R injury were identified, which included eight significantly upregulated miRNAs (miR-let-7b-3p, miR-let-7c-3p, miR-15b-3p, miR-195-3p, miR-21-5p, miR-214-5p, miR-24-3p, and miR-320a) and two significantly downregulated miRNAs (miR-126-5p and miR-499a-5p). They had different influences on myocardial I/R injury. The upregulated target gene-expressing signature messenger RNAs (mRNAs) were mainly involved in the transcriptional regulation process of GO: 0000122, negative regulation of transcription from RNA polymerase II promoter, and so on, while downregulated expression of signature mRNAs was mainly involved in GO:0070534, protein K63-linked ubiquitination, and so forth. To summarize, 10 signature miRNAs of myocardial I/R injury pathogenesis were identified and their target genes and transcription factors were revealed, suggesting the potential novel therapeutic targets for myocardial I/R injury.

Discovering functional impacts of miRNAs in cancers using a causal deep learning model

BackgroundMicro-RNAs (miRNAs) play a significant role in regulating gene expression under physiological and pathological conditions such as cancers. However, it remains a challenging problem to discover the target messenger RNAs (mRNAs) of a miRNA in a data driven fashion. On one hand, sequence-based methods for predicting miRNA targets tend to make too many false positive calls. On the other hand, analyzing expression correlation between miRNAs and mRNAs cannot establish whether relationship between a pair of correlated miRNA and mRNA is causal.MethodsIn this study, we designed a deep learning model, referred to as miRNA causal deep net (mCADET), which aims to explicitly represent two types of statistical relationships between miRNAs and mRNAs: correlation resulting from confounded co-regulation and correlation as a result of causal regulation. The model utilizes a deep neural network to simulate transcription mechanism that leads to co-expression of miRNA and mRNA, and, in addition, it also contains directed edges from miRNAs to mRNAs to capture causal relationships among them.ResultsWe trained the mCADET model using pan-cancer miRNA and mRNA data from The Cancer Genome Atlas (TCGA) project to investigate mechanism of co-expression and causal interactions between miRNAs and mRNAs. Quantitative analyses of the results indicate that the mCADET significantly outperforms conventional deep learning models when modeling combined miRNA and mRNA expression data, indicating its superior capability of capturing the high-order statistical structures in the data. Qualitative analysis of predicted targets of miRNAs indicate that predictions by mCADET agree well with existing knowledge. Finally, the predictions by mCADET have a significantly lower false discovery rate and better overall accuracy in comparison to sequence-based and correlation-based methods when comparing to experimental results.ConclusionThe mCADET model can simultaneously infer the states of cellular signaling system regulating co-expression of miRNAs and mRNAs, while capturing their causal relationships in a data-driven fashion.

Mir-485-3p and Mir-654-3p Expression in Bone Marrow Mesenchymal Stromal Cells in Patients with Monoclonal Gammopathies Is Related to the Status of the Disease

Background: Crosstalk between malignant plasma cells and surrounding cells in the bone marrow (BM), such as mesenchymal stromal cells (MSCs), endothelial cells and immune cells, is crucial for pathogenesis of multiple myeloma (MM) and in asymptomatic monoclonal gammopathies. In these diseases, microRNAs (miRNAs) could be useful as biomarkers for diagnosis, prognosis and evaluation of treatment response. miRNAs can be released to the serum and transferred among MM cells and BM-MSCs as cell-cell communication. Previously, we have showed a serum 14-miRNA signature associated with complete remission (CR) after autologous stem-cell transplantation (ASCT). In this sense, patients in CR with partial recovery of two normal serum miRNA levels, similar to those with monoclonal gammopathy of undetermined significance (MGUS), was associated with better prognosis. The aim of this study was to analyze the miRNAs profile in mesenchymal stromal cells derived from bone marrow of patients with multiple myeloma in different status of the disease, comparing with MGUS controls.Methods: We analyzed samples from 95 patients with MGUS (N=23), MM at diagnosis (N=14), relapsed/refractory MM (N=14), MM in partial response (PR) or very good partial response (VGPR) (N=15), MM in CR (N=24) and healthy donors (N=5). Mononuclear cells from BM samples were cultured in DMEM containing 10% FBS. After a week, non-adherent cells were removed, whereas BM-MSCs were selected by their adherence to the plastic and their phenotype was confirmed by multiparametric flow cytometry. In a first screening phase, we analyzed 670 microRNAs in 20 primary BM-MSC from patients with MGUS (N=4), symptomatic MM (N=8) and MM in CR (N=8). miRNAs differentially expressed were identified according to a supervised analysis using significance analysis of microarrays (SAM) and Student's t-test based on multivariate permutation (with random variance model). miRNAs differentially expressed between groups of patients were validated in the whole cohort of BM-MSC from patients. Paired malignant plasma cells (CD38+) miRNA expression from patients with symptomatic MM as well as miRNA in serum samples paired with BM-MSC samples were also compared. RmiR package was used to identify miRNA targets, cross-correlating the miRNA expression data from the present study with our findings on the gene expression signature (Affymetrix Human Genome U219 array) in 12 BM-MSCs from patients (4 MGUS, 4 symptomatic MM and 4 in CR), based on the predicted targets from TargetScan and miRBase databases.Results: In the screening phase, we identified a miRNA profile of 10 miRNAs (miR-663b, miR-654-3p, miR-206, miR-411*, miR-885-5p, miR-668, miR-638, miR-485-3p, miR-744* and miR-199a) differentially expressed between patients with symptomatic MM and MM in CR (adjusted p-value <0.0001). In the validation phase, miR-485-3p and miR-654-3p resulted differentially expressed in the three groups of patients: MGUS, symptomatic MM and patients in CR (ANOVA test: p=0.0101 and p=0.0228, respectively). The levels of these miRNAs were significantly decreased in patients with MM than in those with MGUS, and these levels seemed to recover when patients achieved CR. These two miRNAs (miR-485-3p and miR-654-3p) were also correlated with all degrees of response in MM and with asymptomatic gammopathies (ANOVA test: p=0.0154 and p=0.0487, respectively). Moreover, paired cross-correlation among these two miRNAs expression with our results in mRNA gene expression profile data showed 324 for miR-485-3p and 265 for miR-654-3p genes (correlation index < -0.8) (Figure 1A and 1B). miR-485-3p and miR-654-3p showed a higher expression in BM-MSC than in MM CD38+ cells, suggesting MSC as cell of origin for these miRNAs. Serum expression of these two miRNAs was concordant with the observed in BM-MSC, with higher in patients in CR and MGUS than in those with symptomatic MM (Figure 1C and 1D). miRNA expression in BM-MSC supernatant as well as the identification of the biological role and validation of the miRNA targets are ongoing.Conclusion: miR-485-3p and miR-654-3p expression in mesenchymal stromal cells from bone marrow in patients with multiple myeloma and asymptomatic monoclonal gammopathies is related to the status of the disease and the response to treatment. These miRNAs are also expressed in serum, resulting in potential biomarkers for disease activity and risk of progression. [Display omitted] DisclosuresRosinol:Janssen, Celgene, Amgen, Takeda: Honoraria. Bladé:Janssen: Honoraria.

Establishment of microRNA, transcript and protein regulatory networks in Alport syndrome induced pluripotent stem cells.

Alport syndrome (AS) is an inherited progressive disease caused by mutations in genes encoding for the α3, α4 and α5 chains, which are an essential component of type IV collagen and are required for formation of the glomerular basement membrane. However, the underlying etiology of AS remains largely unknown, and the aim of the present study was to examine the genetic mechanisms in AS. Induced pluripotent stem cells (iPSCs) were generated from renal tubular cells. The Illumina HiSeq™ 2000 system and iTRAQ-coupled 2D liquid chromatography-tandem mass spectrometry were used to generate the sequences of microRNAs (miRNAs), transcripts and proteins from AS-iPSCs. Integration of miRNA, transcript and protein expression data was used to construct regulatory networks and identify specific miRNA targets amongst the transcripts and proteins. Relative quantitative proteomics using iTRAQ technology revealed 383 differentially abundant proteins, and high-throughput sequencing identified 155 differentially expressed miRNAs and 1,168 differentially expressed transcripts. Potential miRNA targets were predicted using miRanda, TargetScan and Pictar. All target proteins and transcripts were subjected to network analysis with miRNAs. Gene ontology analysis of the miRNAs and their targets revealed functional information on the iPSCs, including biological process and cell signaling. Kyoto Encyclopedia of Genes and Genomes pathways analysis revealed that the transcripts and proteins were primarily enriched in metabolic and cell adhesion molecule pathways. In addition, the network maps identified hsa-miRNA (miR)-4775 as a prominent miRNA that was associated with a number of targets. Similarly, the prominent ELV-like protein 1-A and epidermal growth factor receptor (EGFR)-associated transcripts were identified. Reverse transcription-quantitative polymerase chain reaction analysis was used to confirm the upregulation of hsa-miR-4775 and EGFR. The integrated approach used in the present study provided a comprehensive molecular characterization of AS. The results may also further understanding of the genetic pathogenesis of AS and facilitate the identification of candidate biomarkers for AS.

An integrative transcriptome analysis indicates regulatory mRNA-miRNA networks for residual feed intake in Nelore cattle

Residual Feed Intake (RFI) is an economically relevant trait in beef cattle. Among the molecular regulatory mechanisms, microRNAs (miRNAs) are an important dimension in post-transcriptional regulation and have been associated with different biological pathways. Here, we performed differential miRNAs expression and weighted gene co-expression network analyses (WGCNA) to better understand the complex interactions between miRNAs and mRNAs expressed in bovine skeletal muscle and liver. MiRNA and mRNA expression data were obtained from Nelore steers that were genetically divergent for RFI (N = 10 [low RFI or feed efficient]; N = 10 [high RFI or feed inefficient]). Differentially expressed and hub miRNAs such as bta-miR-486, bta-miR-7, bta-miR15a, bta-miR-21, bta-miR 29, bta- miR-30b, bta-miR-106b, bta-miR-199a-3p, bta-miR-204, and bta-miR 296 may have a potential role in variation of RFI. Functional enrichment analysis of differentially expressed (DE) miRNA’s target genes and miRNA–mRNA correlated modules revealed that insulin, lipid, immune system, oxidative stress and muscle development signaling pathways might potentially be involved in RFI in this population. Our study identified DE miRNAs, miRNA - mRNA regulatory networks and hub miRNAs related to RFI. These findings suggest a possible role of miRNAs in regulation of RFI, providing new insights into the potential molecular mechanisms that control feed efficiency in Nelore cattle.

MiR‑122 promotes proliferation and invasion of clear cell renal cell carcinoma by suppressing Forkhead box O3.

MicroRNAs (miRNAs) serve an important role in renal cancer, but renal cancer miRNA expression data remains inconsistent. Therefore, there is a requirement for integrated analysis of these data. An increasing number of studies demonstrate that miR-122 is dysregulated in numerous cancer types, including liver, lung and breast cancer, yet its role in clear cell renal cell carcinoma (ccRCC) remains unclear. In the present study, an integrated analysis of four ccRCC miRNAs expression datasets was performed and the expression of miR-122 in the present cohort was validated. The effects of cell proliferation, colony formation, migration and invasion of ccRCC cells in vitro were assayed following transfection with miR-122 mimics and inhibitor. The target gene of miR-122 was confirmed using a luciferase reporter assay, and a xenograft mouse model was used to determine the effect of miR-122 in ccRCC tumorigenicity in vivo. The present results demonstrated that patients with ccRCC with an increased miR-122 level in tumor tissues had a shortened metastasis-free survival time as indicated by The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma dataset and the present ccRCC cohort. Overexpression of miR-122 in 786-O cells improved cell proliferation, colony formation, migration and invasion, while knockdown of miR-122 in SN12-PM6 cells inhibited cell growth, colony formation, migration and invasion. Western blot analysis and luciferase reporter assays were used to identify FOXO3 as a direct target of miR-122. The present results indicate that miR-122 serves a tumor-promoting role by direct targeting FOXO3 in ccRCC.

Lung fibroblasts express a miR-19a-19b-20a sub-cluster to suppress TGF-\u03b2-associated fibroblast activation in murine pulmonary fibrosis

Lung fibroblasts play a pivotal role in pulmonary fibrosis, a devastating lung disease, by producing extracellular matrix. MicroRNAs (miRNAs) suppress numerous genes post-transcriptionally; however, the roles of miRNAs in activated fibroblasts in fibrotic lungs remain poorly understood. To elucidate these roles, we performed global miRNA-expression profiling of fibroblasts from bleomycin- and silica-induced fibrotic lungs and investigated the functions of miRNAs in activated lung fibroblasts. Clustering analysis of global miRNA-expression data identified miRNA signatures exhibiting increased expression during fibrosis progression. Among these signatures, we found that a miR-19a-19b-20a sub-cluster suppressed TGF-β-induced activation of fibroblasts in vitro. Moreover, to elucidate whether fibroblast-specific intervention against the sub-cluster modulates pathogenic activation of fibroblasts in fibrotic lungs, we intratracheally transferred the sub-cluster-overexpressing fibroblasts into bleomycin-treated lungs. Global transcriptome analysis of the intratracheally transferred fibroblasts revealed that the sub-cluster not only downregulated expression of TGF-β-associated pro-fibrotic genes, including Acta2, Col1a1, Ctgf, and Serpine1, but also upregulated expression of the anti-fibrotic genes Dcn, Igfbp5, and Mmp3 in activated lung fibroblasts. Collectively, these findings indicated that upregulation of the miR-19a-19b-20a sub-cluster expression in lung fibroblasts counteracted TGF-β-associated pathogenic activation of fibroblasts in murine pulmonary fibrosis.

A potential role of extended simple sequence repeats in competing endogenous RNA crosstalk

ABSTRACTMicroRNA (miRNA)-mediated crosstalk between coding and non-coding RNAs of various types is known as the competing endogenous RNA (ceRNA) concept. Here, we propose that there is a specific variant of the ceRNA language that takes advantage of simple sequence repeat (SSR) wording. We applied bioinformatics tools to identify human transcripts that may be regarded as repeat-associated ceRNAs (raceRNAs). Multiple protein-coding transcripts, transcribed pseudogenes, long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) showing this potential were identified, and numerous miRNAs were predicted to bind to SSRs. We propose that simple repeats expanded in various hereditary neurological diseases may act as sponges for miRNAs containing complementary repeats that would affect raceRNA crosstalk. Based on the representation of specific SSRs in transcripts, expression data for SSR-binding miRNAs and expression profiling data from patients, we determined that raceRNA crosstalk is most likely to be perturbed in the case of myotonic dystrophy type 1 (DM1) and type 2 (DM2).

Architecture of gene regulatory networks controlling flower development in Arabidopsis thaliana

Floral homeotic transcription factors (TFs) act in a combinatorial manner to specify the organ identities in the flower. However, the architecture and the function of the gene regulatory network (GRN) controlling floral organ specification is still poorly understood. In particular, the interconnections of homeotic TFs, microRNAs (miRNAs) and other factors controlling organ initiation and growth have not been studied systematically so far. Here, using a combination of genome-wide TF binding, mRNA and miRNA expression data, we reconstruct the dynamic GRN controlling floral meristem development and organ differentiation. We identify prevalent feed-forward loops (FFLs) mediated by floral homeotic TFs and miRNAs that regulate common targets. Experimental validation of a coherent FFL shows that petal size is controlled by the SEPALLATA3-regulated miR319/TCP4 module. We further show that combinatorial DNA-binding of homeotic factors and selected other TFs is predictive of organ-specific patterns of gene expression. Our results provide a valuable resource for studying molecular regulatory processes underlying floral organ specification in plants.

Discovering the \u2018Dark matters\u2019 in expression data of miRNA based on the miRNA-mRNA and miRNA-lncRNA networks

BackgroundSince miRNAs can play important roles in different cancer types, how to discover cancer related miRNAs is an important issue. In general, the miRNAs with differential expression is the focus of attention. However, some important cancer related miRNAs are not excavated by differential expression analysis. We take this type of miRNAs as ‘dark matters’ (DM-miRNA). It is our great interests to develop an algorithm to discover DM-miRNAs.ResultsAn effective method was developed to find DM-miRNAs. This method is mainly for mining potential DM-miRNAs by building basic miRNA-mRNA network (BMMN) and miRNA-lncRNA network (BMLN). The results indicate that miRNA-mRNA and miRNA-lncRNA interactions can be used as novel cancer biomarkers.ConclusionsThe BMMN and BMLN can excavate the non-differentially expressed miRNAs which play an important role in the cancer. What’s more, the edge biomarkers (miRNA-mRNA and miRNA-lncRNA interactions) contain more information than the node biomarkers. It will contribute to developing novel therapeutic candidates in cancers.

Identification of miR-200c and miR141-Mediated lncRNA-mRNA Crosstalks in Muscle-Invasive Bladder Cancer Subtypes.

Basal and luminal subtypes of muscle-invasive bladder cancer (MIBC) have distinct molecular profiles and heterogeneous clinical behaviors. The interactions between mRNAs and lncRNAs, which might be regulated by miRNAs, have crucial roles in many cancers. However, the miRNA-dependent crosstalk between lncRNA and mRNA in specific MIBC subtypes still remains unclear. In this study, we first classified MIBC into two conservative subtypes using miRNA, mRNA and lncRNA expression data derived from The Cancer Genome Atlas. Then we investigated subtype-related biological pathways and evaluated the subtype classification performance using Decision Trees, Random Forest and eXtreme Gradient Boosting (XGBoost). At last, we explored potential miRNA-mediated lncRNA-mRNA crosstalks based on co-expression analysis. Our results show that: (1) the luminal subtype is primarily characterized by upregulation of metabolism-related pathways while the basal subtype is predominantly characterized by upregulation of epithelial-mesenchymal transition, metastasis, and immune system process-related pathways; (2) the XGBoost prediction model is consistently robust for classification of the molecular subtypes of MIBC across four datasets (The area under the ROC curve > 0.9); (3) the expression levels of the molecules in the miR-200c and miR141-mediated lncRNA-mRNA crosstalks differ considerably between the two subtypes and have close relationships with the prognosis of MIBC. The miR-200c and miR-141-dependent mRNA-lncRNA crosstalks might be of great significance in tumorigenesis and tumor progression and may serve as the novel prognostic predictors and classification markers of MIBC subtypes.

MiARma-Seq, a comprehensive pipeline for the simultaneous study and integration of miRNA and mRNA expression data.

Messenger RNAs (mRNAs) fulfil specific biological roles in cells and, thus, their expression may be adapted to suit specific circumstances. This is in part achieved through selective gene transcription and post-transcriptional events, the regulation of which must be tightly integrated and controlled. To comprehensively study the coordinated effects of transcriptional and post-transcriptional regulatory elements, and to obtain coherent results, it is advisable to use different methodologies. Adequately integrating the data derived from these distinct methodologies then becomes critical to elucidating the relationships between the coordinated cellular effects assayed, particularly when applied to normal and disease states. Such integrated studies are likely to be particularly useful to identify markers suitable for early detection of diseases and to devise strategies for therapeutic interventions. Throughout this chapter, we will focus on the methods currently available to analyse mRNA and microRNA (miRNA) expression, paying special attention to the influence of miRNAs on mRNA metabolism. We will introduce miARma-Seq, a comprehensive pipeline that facilitates the simultaneous integration of mRNA and miRNA expression data. For illustrative purposes, we include a case study that incorporates data from RNASeq and small-RNASeq, detailing all the steps necessary to define the differential expression of both mRNA- and miRNA-encoding genes. Finally, we explore the possible regulatory relationships that drive significant and potentially relevant changes in mRNA and miRNA gene expression.

A novel bayesian multiple testing approach to deregulated miRNA discovery harnessing positional clustering.

MicroRNAs (miRNAs) are small non-coding RNAs that function as regulators of gene expression. In recent years, there has been a tremendous interest among researchers to investigate the role of miRNAs in normal as well as in disease processes. To investigate the role of miRNAs in oral cancer, we analyse expression levels of miRNAs to identify miRNAs with statistically significant differential expression in cancer tissues. In this article, we propose a novel Bayesian hierarchical model of miRNA expression data. Compelling evidence has demonstrated that the transcription process of miRNAs in the human genome is a latent process instrumental for the observed expression levels. We take into account positional clustering of the miRNAs in the analysis and model the latent transcription phenomenon nonparametrically by an appropriate Gaussian process. For the purpose of testing, we employ a novel Bayesian multiple testing method where we mainly focus on utilizing the dependence structure between the hypotheses for better results, while also ensuring optimality in many respects. Indeed, our non-marginal method yielded results in accordance with the underlying scientific knowledge which are found to be missed by the very popular Benjamini-Hochberg method.

Functional Role of microRNA-23b-3p in Cancer Biology.

MicroRNAs (miRNAs) constitute a class of short non coding RNAs that have crucial biological roles by acting mainly as negative regulators of gene expression. The alteration of miRNAs expression has been frequently demonstrated in cancer. Furthermore, miRNAs expression data clearly revealed their possible use as diagnostic, prognostic and predictive biomarkers. In this review, we focus on the biological role of human miR-23b-3p in cancer. Several data demonstrated that miR-23b-3p targeted different genes involved in cancer aggressive properties such as proliferation, migration, invasion, and metastasis. In this context, it is known that miR-23b-3p, as other miRNAs, can target either tumor-suppressor genes or oncogenes in different types of tumors. Therefore, its net biological effect can be tumor-specific, mainly depending on the consequent alterations on the downstream effects of the altered pathways. MiR-23b-3p has been found down-regulated or up-regulated in primary tumors and dysregulated in plasma and serum of cancer patients. Its expression levels correlate with the overall survival, disease-free survival and prognosis in several malignancies, thus assuming a remarkable role as molecular biomarker with clinical relevance. Finally, miR-23b-3p is generally considered a responsive molecular therapeutic target as reported in several in vitro and in vivo studies. This suggests that the ectopic modulation of its expression may potentially be important for translational medicine approaches.

Identification of optimal reference RNAs to normalize miRNA expression data by qRT-PCR in formalin-fixed, paraffin-embedded lymph node tissue

Identification of optimal reference RNAs to normalize miRNA expression data by qRT-PCR in formalin-fixed, paraffin-embedded lymph node tissue

Tree-based machine learning algorithms identified minimal set of miRNA biomarkers for breast cancer diagnosis and molecular subtyping

Breast cancer is a complex disease and its effective treatment needs affordable diagnosis and subtyping signatures. While the use of machine learning approach in clinical computation biology is still in its infancy, the prevalent approach in identifying molecular biomarkers remains to be screening of all biomarkers by differential expression analysis. Many of these attempts used miRNAs expression data in breast cancer and amounted to the multitude of differentially expressed miRNAs in this cancer; hence, the minimal set of miRNA biomarkers to classify breast cancer is yet to be identified.Availability of diverse and vast amount of cancer datasets like The Cancer Genome Atlas facilitated the molecular profiling of patients' tumors and introduced new challenges like clinical grade interpretations from big data. In this study, miRNA expression dataset of breast cancer patients from TCGA database was used to develop prediction models from which miRNA biomarkers were identified for diagnosis and molecular subtyping of this cancer. I took the advantage of interpretability of tree-based classification models to extract their rules and identify minimal set of biomarkers in this cancer.Empirical negative control miRNAs in breast cancer obtained and used to normalize the dataset. Tree-based machine learning models trained in my analysis used hsa-miR-139 with hsa-miR-183 to classify breast tumors from normal samples, and hsa-miR4728 with hsa-miR190b to further classify these tumors into three major subtypes of breast cancer. In addition to the proposed biomarkers, the most important miRNAs in breast cancer classification were also presented.

Identification of optimal reference RNAs to normalize miRNA expression data by qRT-PCR in formalin-fixed, paraffin-embedded lymph node tissue

We recently read the interesting paper of Inada et al ., published on Sci Rep 2018 (1), regarding the identification of optimal reference RNAs for miRNA quantification using qRT-PCR in formalin-fixed paraffin-embedded (FFPE) lymph node tissues from patients with metastatic cancer.

MiR-5590-3p inhibited tumor growth in gastric cancer by targeting DDX5/AKT/m-TOR pathway

Recent evidence suggests that microRNAs play important roles in the negative post-transcriptional regulators with altered expression levels found in gastric cancer (GC). Therefore, we employed explore the anti-cancer miRNA and the potential mechanisms by which miRNAs modulate GC progression. We have predicted GC miRNA expression data sets in TargetScan. miR-5590-3p is higher in adjacent nonmalignant tissue than in cancer tissue in 42 pairs of GC tissues. Functional assays, CCK-8 and colony formation assay, were used to determine the Anti-cancer role of miR-5590-3p in human GC progression. In addition, Ago2-based RIP and dual-luciferase reporter assay were conducted to study the miR-5590-3p as a direct target of DDX5. Next, Xenograft nude mouse models were used to determine the role of miR-5590-3p in GC tumorigenicity in vivo. Upregulation of miR-5590-3p suppressed GC cell proliferation, whereas downregulation of miR-5590-3p promoted GC proliferation in vitro. Furthermore, we identified DDX5 as a direct target of miR-5590-3p, and that the biological function of miR-5590-3p during GC progression in vitro and in vivo is through the DDX5/AKT/m-TOR pathway and downstream cyclinD1 and CDK2 expression. Finally, we confirmed the effect of miR-5590-3p directly targeting DDX5 on the development of gastric cancer through salvage experiments in vivo and in vitro.

PO-194 Identification of regulatory circuits specific to breast cancer development by enrichment based circuit finder

IntroductionGene expression mechanism is regulated by transcriptional factors (TF) in transcriptional level and by miRNAs in post-transcriptional level. Transcription of mRNAs and miRNAs are controlled by TFs and TF expressions are regulated by miRNAs. Characterisation of these regulatory mechanisms in the cell is crucial to understand the diseases like breast cancer. For this purpose we have developed an enrichment based circuit finder and applied it to breast cancer data.Material and methodsThe system developed for the detection of active regulatory circuits (miRNA-TF-gene) in breast cancer formation has two analysis lines. The first one is ’local network analysis’. This step of the system involves determining the specific dual probabilities like TF-gene or miRNA-gene. The second line of analysis is the ’global network analysis’, in which global relations are obtained from existing databases. Differentially expression (DE) analysis is implemented for mRNA and miRNA expression data. According to this analysis, differentially expressed genes and miRNAs between tumour and normal samples are listed and transferred to next step. All studies in the literature, which are related with regulatory circuits, TF, miRNA and gene lists are selected based only on DE analysis. However, this may be resulted with missing significant network nodes which is not altered significantly between the two cases like tumour and normal. For this reason, GSEA (Gene Set Enrichment Analysis) and miSEA analyses were performed in order to determine TFs and miRNAs, which are not included in DE lists but enriched in the gene/miRNA clusters.Results and discussionsAs a result 128 closed loop circuits were obtained. mir17 family, mir106b-25 cluster, mir17-92 cluster, mir106a-363 cluster members and E2Fs constituted the major part of the members in these circuits. These regulatory elements were found to take part in cancer related pathways like apoptosis, cell cycle and p53. hsa-miR-16-E2F1-VEGFA was the most prominent of the circuits identified, which was also concordant with the existing studies on breast cancer in the literature. This indicated that other circuit members in the list may also be potential biomarker candidates that are not yet associated with breast cancer.ConclusionIn summary, our tool enabled us to investigate regulatory circuits in breast cancer development and significant results were obtained. Identification of the new circuits may provide further possibility to improve our information about breast cancer development and progression.

Abstract 4416: MiRNAs genes are regulated by methylation in papillary thyroid carcinomas

Abstract Background: Papillary thyroid cancer (PTC) is the most common thyroid malignancy. DNA methylation associated with microRNAs (miRNA) regulation is an effective epigenetic mechanism for controlling gene expression. This mechanism is poorly explored in PTC. Patients and Methods: To investigate miRNAs genes regulated by methylation, global DNA methylation (Infinium® Human Methylation450 BeadChip, Illumina) analysis was performed in 50 matched PTC and normal tissues (NT) and compared with those deposited in The Cancer Genome Atlas (TCGA) (515 PTC and 56 NT). An integrative analysis was performed in 510 cases evaluated by whole methylation and miRNA expression analysis (TCGA). Using these findings, three miRNAs were investigated by RT-qPCR and pyrosequencing in PTC (N=103), normal thyroid tissues (NT, N=40) and benign thyroid lesions (BTL, N=32). In addition, seven target genes of these miRNAs were evaluated by RT-qPCR (44PTC, 30BTL and 28NT). Functional assays using three PTC cell lines (TPC1, K1 and BCPAP) were used to investigate the role of methylation in the miRNAs expression. Results: We found 50 differentially methylated probes of which 42 (27 microRNA genes) were confirmed in the TCGA database. The miRNA expression data from TCGA presented 67 differentially expressed miRNAs in PTC. The integrative analysis revealed three miRNAs (hsa-miR-146b-5p, hsa-miR-146b-3p and hsa-miR-21-5p) as candidates to be regulated by methylation. A significant hypomethylation pattern in PTC compared to NT and BTL (thyroid benign lesions) was found for these three miRNAs. Increased expression levels of hsa-miR-21-5p and hsa-miR-146b-5p were detected in PTC compared to NT and BTL. Combining these two miRNAs expression values, 45/47 PTC were distinguished from 66/67 non-malignant tissues (96% sensitivity and 99% specificity). Similarly, the association of methylation and expression data distinguished 41/45 PTC from 55/60 non-malignant tissues (91% sensitivity and 92% specificity) for MIR21 gene and 45/47 PTC from 61/61 NT/BTL (96% sensitivity and 100% specificity) for MIR146B gene. Seven target genes (MPPED2, STXBP5L, MRO, FHL1, FLRT1, DOK6 and MOB3B) of these miRNAs were significantly down regulated in PTC compared to NT and BTL. The BRAFV600E mutation was significantly associated to hypomethylation and overexpression of hsa-miR-21-5p and hsa-miR-146b-5p. Methylation and expression data in these three cell lines revealed that MIR146B is putatively regulated by methylation. Conclusion: We provide evidences that MIR21 and MIR146B genes are regulated by methylation having control in the expression of target genes associated with PTC. These miRNAs have a strong potential to be used as diagnostic markers in the clinical practice. Citation Format: Isabella Maria D. Ortiz, Mateus de Camargo Barros-Filho, Mariana B. dos Reis, Caroline Moraes Beltrami, Fabio Albuquerque Marchi, Hellen Kuasne, Clovis Pinto, Luiz Kowalski, Silvia Rogatto. MiRNAs genes are regulated by methylation in papillary thyroid carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4416.